Network visualization through augmented reality and modeling

ABSTRACT

A user equipment (UE) comprising a display, an input device configured to receive user input, a visual input configured to capture motion or stop photography as visual data, and a processor coupled to the display, input device, and visual input and configured to, receive visual data from the visual input, overlay a model comprising network data onto the visual data to create a composite image, wherein the model is aligned to the visual data based on user input received from the input device, and transmit the composite image to the display.

CROSS-REFERENCE TO RELATED APPLICATIONS

Not applicable.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not applicable.

REFERENCE TO A MICROFICHE APPENDIX

Not applicable.

BACKGROUND

In order to perform network layout planning, optimization, andmaintenance, network technicians may be required to locate and ascertainthe status of the network's elements (NEs). This process may becomeproblematic in situations where the network comprises many NEs, thetechnician is unfamiliar with the facility that houses the network,network components are obscured from view, and/or network components arenot clearly labeled. These problems may be exacerbated by theutilization of mobile network elements that may be moved around thefacility by other users. Such mobile network elements may not remain inpredictable locations and may be difficult to locate on demand.

SUMMARY

In one embodiment, the disclosure includes a user equipment (UE)comprising a display, an input device configured to receive user input,a visual input configured to capture motion or stop photography asvisual data, and a processor coupled to the display, input device, andvisual input and configured to, receive visual data from the visualinput, overlay a model comprising network data onto the visual data tocreate a composite image, wherein the model is aligned to the visualdata based on user input received from the input device, and transmitthe composite image to the display.

In another embodiment, the disclosure includes a method comprisingimporting a model of a location, wherein the location comprises aplurality of physical features, and wherein the model comprises aplurality of features that represent the physical features of thelocation, overlaying the model onto a first visual data received from avisual input to create a first composite image and displaying the firstcomposite image to a user, receiving from the user, via an input device,a first user input that aligns a feature of the model with a physicalfeature of the location in the first visual data, and overlaying themodel, as aligned by the user, onto a second visual data received fromthe visual input to create a second composite image and displaying thesecond composite image to the user.

These and other features will be more clearly understood from thefollowing detailed description taken in conjunction with theaccompanying drawings and claims.

BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of this disclosure, reference is nowmade to the following brief description, taken in connection with theaccompanying drawings and detailed description, wherein like referencenumerals represent like parts.

FIG. 1 is a schematic diagram of a network architecture for supportingnetwork visualization by a UE.

FIG. 2 is a flowchart of a method of overlaying a model comprisingnetwork data onto visual data.

FIG. 3 is a schematic diagram of an embodiment of a model of a location.

FIG. 4 is illustration of an embodiment of a UE being calibrated.

FIG. 5 is a schematic diagram of an object described by roll, pitch, andyaw.

FIG. 6 is a depiction of a congruence between a model and a UE aftercalibration.

FIG. 7 is a schematic diagram of an embodiment of a model of a locationcomprising network data.

FIG. 8 is a schematic diagram of an embodiment of a composite imagecomprising network data.

FIG. 9 is a schematic diagram of an embodiment of a UE.

FIG. 10 is a schematic diagram of an embodiment of a NE.

DETAILED DESCRIPTION

It should be understood at the outset that, although an illustrativeimplementation of one or more embodiments are provided below, thedisclosed systems and/or methods may be implemented using any number oftechniques, whether currently known or in existence. The disclosureshould in no way be limited to the illustrative implementations,drawings, and techniques illustrated below, including the exemplarydesigns and implementations illustrated and described herein, but may bemodified within the scope of the appended claims along with their fullscope of equivalents.

Disclosed herein is a system and method for accurately displaying thephysical position of NEs. A user may employ a UE that comprises a visualinput, such as a camera, a display, a data input, and position sensors.The UE may import a model of a location, such as a three dimensional(3D) model of a building, from a database and allow the user to selectthe UE's approximate position on the model. The database may be storedon the UE or on a profile server accessible to the UE. The UE mayoverlay the model onto visual data from the visual input to create acomposite image for display to the user. The user may calibrate the UEvia the data input by aligning a portion of the model with a feature ofthe location. The UE may access a network layout from the database andload the layout onto the model. The UE may overlay the NEs and anyassociated network data onto the visual data from the visual input tocreate a composite image for display to the user. The location of theNEs on the composite image may be determined by a correlation betweenthe model and the location based on the calibration. As the user movesthe UE, data from UE's position sensors may be employed to determine thenature of the UE movement, and the location of the network data on thecomposite image may be adjusted accordingly. The model may or may not bedisplayed to the user once calibration is complete. The location of theNE's as displayed by the UE may be accurate to within about 0.5 metersto about 1 meter, about 1 meter to about 3 meters, or about 0.5 metersto about 3 meters.

FIG. 1 is a schematic diagram of a network architecture 100 forsupporting network visualization by a UE 110. The network 100 maycomprise a server 122 connected to NEs 130-131 via access points (APs)121, which may also be considered NEs. The UE 110 and NEs 130-131 mayconnect to the server 122 via the APs 121 via wired (e.g. NE 131) orwireless (e.g. NE 130) communication.

The NEs 130-131 may comprise UEs, computers, printers, routers,switches, wireless access points, servers, and/or other networkcomponents that support the connectivity of UEs to the network 100. NE's130-131 may also support the connectivity of UEs to the Internet via thenetwork 100. NE 131 may connect to an AP 121 via a wired connection,while NE 130 may connect to an AP 121 via a wireless connection. As awired device, the physical location of NE 131 may remain relativelyconstant while the physical location of wireless NE 130 may change overtime based on user movement. The NEs 130-131 may be assigned Ethernetinternet protocol (IP) addresses, subnet masks, and/or other identifyingconnectivity information to support network communication. Each NE mayfurther comprise ports and/or interfaces which may be designated by theNE and/or network and employed to connect to the other networkcomponents via wired links, wireless connections, etc.

The IP addresses, connectivity information, port designations, interfacedesignations, and/or link information of the NE's 130-131 and APs 121may be collected by the server 122 and stored as network data. Theserver 122 may also collect, calculate, and/or store as network data thephysical locations of the NE's 130-131 and/or APs 121 at a specifiedtime (e.g. via Global Positioning System (GPS) sensors installed in theNE's 130-131 and/or APs 121, triangulation based on network signals,etc.) The server 122 may update the network data that comprises thephysical location of an NE (e.g. wireless NE 130) as the NE is moved bya user (e.g. the physical location changes) in the normal course ofoperation. Such updates may be event based and/or periodic. In additionor in the alternative, the server 122 may store key performanceindicators (KPIs) associated with the NEs 130-131, APs 121, and/orrelated links as network data. KPIs may encompass a broad range ofindicators and/or metrics that are designed to indicate the connectivitystatus of an NE. As a non-limiting example, KPIs may include deviceavailability, interface availability, link availability, bandwidthusage, link performance, data latency, quality of service (QoS)statistics, packet loss, device health, routing statistics, deviceuptime, etc. KPIs may also vary based on network implementation and maybe customized to indicate various aspects of NE and/or network health.

UE 110 may be employed by a user, such as a network technician thatwishes to visualize the network 100. The UE 110 may comprise a visualinput, such as a still or video camera capable of capturing motion orstop photography as visual data. The UE 110 may also comprise a displayconfigured to display visual data, and an input device for receivinguser input. The UE 110 may import a model of a location that comprisesall or part of the network 100. The model may also comprise network dataassociated with NE's 130-131 and/or APs 121. The model and/or thenetwork data may be received from the server 122, stored in memory atthe UE 110, or combinations thereof. The UE 110 may overlay the modelonto the visual data from the visual input to create a composite image(e.g. a single image or video images). The UE 110 may then display thecomposite image comprising the network data to the user via the display.The user may calibrate the UE 110 by aligning a feature of the model(e.g. a corner or a wall of a model building) with a feature of thelocation captured in the visual data (e.g. a corresponding corner orwall of building) via the input device. The UE 110 may also compriseposition sensors such as global position system (GPS) sensors,magnetometers, accelerometers, gyroscopes, and/or other sensors, whichmay indicate the position and/or motion of the UE 110 as position ormotion data. Once calibrated, the UE 110 may maintain a congruencebetween the model and the location as the UE 110 moves so that thenetwork data may appear in an accurate position relative to the user'spoint of view. The UE 110 may maintain the congruence by moving themodel to correspond to the movement of the UE as indicated by theposition sensors.

FIG. 2 is a flowchart of a method 200 of overlaying a model comprisingnetwork data onto visual data, for example by a UE such as UE 110. Atblock 201, the UE may import a model of a location. A location may be ageographical, topographical, or other designated area on the Earth'ssurface. A model of a location may be a three dimensional (3D) or twodimensional (2D) representation of the location. For example, a networksuch as network 100 may be housed in a building and UE 110 may import a3D architectural model of the building. The method may then proceed toblock 202.

At block 202, the UE may overlay the model onto visual data captured bythe UE's visual input to create a composite image and display thecomposite image to the user. The model may be overlaid based on userinput or based on data from position sensors. For example, the model maybe displayed to the user, and the user may be prompted to select aposition on the model that approximates the user's position in thelocation. As an additional or alternative example, the model maycomprise position data such as GPS coordinates of points on the modelthat correspond to points at the location. The UE may compare positiondata from the UE's position sensors to the position data of the model todetermine the initial position of the model. Once the model ispositioned relative to the user, the UE may overlay the model ontovisual data to approximate the user's point of view and proceed to block203.

At block 203, the UE may prompt the user to calibrate the UE by aligningthe model with visual data of the location as captured by the visualinput. For example, the location may comprise a plurality of easilydistinguishable physical features such as walls, floors, corners, etc.The model may comprise features that represent and correspond to thephysical features of the location. The user may alter the orientation ofthe model, the angle of the model, and/or the apparent size of the modelby spinning the model in two or three dimensions, zooming the view ofthe model in or out, etc. The user may continue to alter the view of themodel until one or more features of the model appear to closelycorrespond with the physical features of the location. Once acorrespondence between the model and the location has been determined,the UE may be configured to accurately overlay the model onto the visualdata from the visual input so that portions of the model appear in thesame position as portions of the location relative to the user's pointof view. The model may be displayed in a semitransparent fashion to aidin calibration. Once calibration is completed, the method 200 mayproceed to block 204.

At block 204, the UE may load network data into the model from adatabase. The database and/or model may be stored in UE memory, in whichcase dynamic network data may be unavailable. Alternatively, thedatabase and/or model may be stored on a server and transmitted to theUE periodically or on demand, in which case dynamic network data may beavailable, but may be subject to latency. In yet another alternative,portions of the database and/or model may be continuously streamed tothe UE via a wired or wireless connection. The network data may comprisethe position of NE's relative to the model and the network data may beused to place the NE's and network data associated with each NE into theappropriate position(s) in the model. The method may then proceed toblock 205.

At block 205, the UE may overlay the model and/or associated networkdata onto the visual data to create a composite image and may displaythe composite image to the user. The model may be visible,semitransparent, or completely transparent, depending on theimplementation and/or the user's preference. Regardless of thetransparency of the model, the network data positioned on the model maybe displayed to the user. For example, the user may view the display ofthe UE, and the network data may appear in approximately the sameposition relative the user as the NE associated with the network data.By viewing the display, the user may ‘view’ NEs that are obscured fromactual view by walls, drawers, etc. The UE may move the model inaccordance with the movement of the UE, which may cause the positions ofthe NEs to remain in proper position relative to the user's point ofview as the UE moves. The use of a model to position the NEs may resultin NE positioning that is accurate to within about 0.5 meters to about 1meter, about 1 meter to about 3 meters, or about 0.5 meters to about 3meters.

FIG. 3 is a schematic diagram of an embodiment of a model 300 of alocation, which may be imported at block 201 of method 200. The model300 may be a 3D representation of the location, for example a floorplan. The model 300 may comprise features that correspond to physicalfeatures associated with the location, for example internal walls 310,external walls 311, floor space 312, corners 313 where features connect,and/or doorways 314. The features of the model 310-314 may be alignedwith the physical features of the location to calibrate a UE, forexample in method 200.

FIG. 4 is an illustration 400 of an embodiment of a UE 410 beingcalibrated, for example at block 203 of method 200. UE 410 may besubstantially similar to UE 110 and may comprise a display 411. The UE410 may be employed in a location 430. The location 430 may havephysical features 431 such as walls, corners, ceilings, floors, etc. Thedisplay 411 may comprise a model 420, which may be substantially similarto model 300 and may be overlaid onto visual data and displayed to auser at block 202 of method 200. The model 420 may comprise features 421that correspond to the physical features 431 of the location 430, suchas walls, corners, ceilings, floors, etc. The user may calibrate the UE410 by aligning a feature 421 of the model 420 with a physical feature431 of the location 430. For example, the user may align a wall of themodel 420 with a wall of the location 430 in the UE display 411. Theuser may rotate the model in three dimensions as well as zoom in and outuntil the location and size of the model features 421 approximatelymatch the location features 431.

FIG. 5 is a schematic diagram of an object 500 described by roll 501,pitch 502, and yaw 503. The rotation of an object 500 in a threedimensional space may be described in terms of angles of roll 501, pitch502, yaw 503, and/or combinations thereof. The rotation of an objectaround a longitudinal axis, a lateral axis, and a vertical axis, may bedescribed as changes in the angle of roll 501, pitch 502, and yaw 503,respectively.

FIG. 6 is a depiction 600 of a congruence between a model, such as model300, and a UE, such as UE 310, after calibration (e.g. block 203 ofmethod 200). The orientation of a UE may be described by the angles yaw,pitch, and roll (e.g. roll 501, pitch 502, and yaw 503). The primaryangle (α) 601 (e.g. roll, pitch, or yaw) of a UE visual input to aphysical feature in a location may be related to the size of the feature(S) 610 and distance to the feature (D) 603 by the equationS=2*D*tan(α/2) when the center of the visual input is pointing at themid-point of the feature. When the center of the visual input is notpointing at the mid-point of the feature, the relationship may bedescribed by the equation S=D*tan(β)+D*tan(α−β), where secondary angle(β) 602 is the angle between the midpoint of the feature and the pointto which the center of the visual input is pointing. Calibration (e.g.block 203) may determine α 601, β 602, and/or D 603.

D 603 may be calculated when a physical feature in the visual data and afeature of the model are aligned because aligning the features may causeS 610, α 601, and β 602 of the physical feature and the model feature tomatch. The distance (e.g. D 603) between the UE and the feature may beused to determine the position of the UE relative to the feature and maybe used to position the model features relative to the visual data. Theview of the model may then be moved based on position and/or motion datafrom the position sensors to maintain a congruence between the model andthe location.

When the UE moves, the angle of rotation (e.g. roll, pitch, or yaw) asmeasured by the position sensors of the UE (A) may be related to theactual angle of rotation (A′) by the equation A′=A+ΔA(A, t) where ΔA isthe error of the measurement over time (t). Such measurement errors mayfluctuate over time and orientation based on the implementation of theposition sensors (e.g. gyroscope, magnetometer, etc.) At any t, the UEmay be calibrated by rotating a view of the model to match the visualinput view, which may offset the measured A′ with ΔA to get the actualA. Because ΔA(A, t) is a function of A and t, ΔA may fluctuate over timeat the same orientation and ΔA may fluctuate as the UE changesorientation. Averaging consecutive measurements may reduce randomfluctuations in ΔA over time. Orientation based fluctuation may besolved by requiring additional calibration via alignment.

FIG. 7 is a schematic diagram of an embodiment of a model 700 of alocation comprising network data. For example, model 700 may besubstantially similar to model 300, but may comprise network data as theresult of block 204 of method 200. The model 700 may comprise NEs 710and NE transmission ranges 720. A UE and/or server may load the NEs 710and transmission ranges 720 onto model 300, for example at block 204,which may result in model 700. The NEs 710 and transmission ranges 720may be loaded onto the model based on the current position of the NEs710 and/or based on a fixed position for each NE 710. Model 700 maycomprise additional network data as needed in a particularimplementation.

FIG. 8 is a schematic diagram of an embodiment of a composite image 800comprising network data 820. Composite image 800 may be the result ofblock 205 of method 200. A model comprising the network data 820 may beoverlaid onto visual data and displayed on the display 811 of a UE 810,which may be substantially similar to UE 110 and/or UE 410. The modelmay be transparent so that only the network data 820 and the visual datamay be perceived by the user. The congruence between the transparentmodel and the location may be maintained during UE movement as discussedabove. As the network data may be loaded into the model, the position ofthe network data may be maintained relative to the NEs in the location.As a result, the user may view NEs in the visual data on the displaythat may be obscured from view by features of the location.

For example, the visual input of a UE may comprise a video camera. Auser may point the video camera at an object or structure such as awall, a desk, a ceiling, etc. If a NE (e.g. NE 130) is located behindthe object, the video camera of the UE may not record the NE (e.g. asvisual data) because the NE is obscured from view. However, the networkdata associated with the NE may indicate the physical location of theNE, which may allow the UE to overlay a representation of the NE and/orthe NE's network data onto video recorded by the NE to create acomposite image (e.g. a single image or a composite video). Thecomposite image may then be displayed to the user, which may allow theuser to see representations of the obscured NE.

FIG. 9 is a schematic diagram of an embodiment of a UE 900. UE 900 maycomprise a two-way wireless communication device having voice and/ordata communication capabilities. In some aspects, voice communicationcapabilities are optional. The UE 900 generally has the capability tocommunicate with other computer systems on the Internet and/or othernetworks. Depending on the exact functionality provided, the UE 900 maybe referred to as a data messaging device, a tablet computer, a two-waypager, a wireless e-mail device, a cellular telephone with datamessaging capabilities, a wireless Internet appliance, a wirelessdevice, a smart phone, a mobile device, or a data communication device,as examples.

UE 900 may comprise a processor 920 (which may be referred to as acentral processor unit or CPU) that may be in communication with memorydevices including secondary storage 921, read only memory (ROM) 922, andrandom access memory (RAM) 923. The processor 920 may be implemented asone or more CPU chips, one or more cores (e.g., a multi-core processor),or may be part of one or more application specific integrated circuits(ASICs) and/or digital signal processors (DSPs). The processor 920 maybe configured to implement any of the schemes described herein, and maybe implemented using hardware, software, firmware, or combinationsthereof.

The secondary storage 921 may be comprised of one or more solid statedrives and/or disk drives which may be used for non-volatile storage ofdata and as an over-flow data storage device if RAM 923 is not largeenough to hold all working data. Secondary storage 921 may be used tostore programs that are loaded into RAM 923 when such programs areselected for execution. The ROM 922 may be used to store instructionsand perhaps data that are read during program execution. ROM 922 may bea non-volatile memory device may have a small memory capacity relativeto the larger memory capacity of secondary storage 921. The RAM 923 maybe used to store volatile data and perhaps to store instructions. Accessto both ROM 922 and RAM 923 may be faster than to secondary storage 921.

UE 900 may be any device that communicates data (e.g., packets)wirelessly with a network. The UE 900 may comprise a receiver (Rx) 912,which may be configured for receiving data, packets, or frames fromother components. The receiver 912 may be coupled to the processor 920,which may be configured to process the data and determine to whichcomponents the data is to be sent. The UE 900 may also comprise atransmitter (Tx) 932 coupled to the processor 920 and configured fortransmitting data, packets, or frames to other components. The receiver912 and transmitter 932 may be coupled to an antenna 930, which may beconfigured to receive and transmit wireless (radio) signals.

The UE 900 may also comprise a device display 940 coupled to theprocessor 920, for displaying output thereof to a user. The devicedisplay 920 may comprise a Color Super Twisted Nematic (CSTN) display, athin film transistor (TFT) display, a thin film diode (TFD) display, alight emitting diode (LED) display, an organic light-emitting diode(OLED) display, an active-matrix OLED display, or any other displayscreen. The device display 940 may display in color or monochrome andmay be equipped with a touch sensor based on resistive and/or capacitivetechnologies.

The UE 900 may further comprise input devices 941, coupled to theprocessor 920, which may allow the user to input commands to the UE 900.In the case that the display device 940 comprises a touch sensor, thedisplay device 940 may also be considered an input device 941. Inaddition to and/or in the alternative, an input device 941 may comprisea mouse, trackball, built-in keyboard, external keyboard, and/or anyother device that a user may employ to interact with the UE 900.

The UE may further comprise a visual input 960 configured to capturemotion or stop photography in the visual input's 960 field of view asvisual data. For example, the visual input 960 may comprise a videocamera or still camera. The visual input 960 may be coupled to theprocessor 920, and may forward visual data captured by the visual input960 to the processor for processing, storage, transmission, and/ordisplay.

The UE 900 may further comprise position sensors 950. Position sensors950 may be coupled to the processor and may be configured to determinethe physical location, height, vertical facing and/or horizontal facingof the UE 900 and/or of the visual input 960 (e.g. field of view data)at a given time. Position sensors 950 may comprise global positionsystem (GPS) sensors, magnetometers, accelerometers, gyroscopes, and/orother sensors. Position sensors 950 may collect and transmit positionand/or motion data collected to the processor 920 to indicate a changein the UE's 900 position and/or motion experience by the UE 900,respectively.

FIG. 10 is a schematic diagram of an embodiment of an NE 1000, which mayfunction as a NE in network 100 and may be employed to implement NE130-131, server 122, and/or an AP 121. One skilled in the art willrecognize that the term NE encompasses a broad range of devices of whichNE 1000 is merely an example. NE 1000 is included for purposes ofclarity of discussion, but is in no way meant to limit the applicationof the present disclosure to a particular NE embodiment or class of NEembodiments. At least some of the features/methods described in thedisclosure may be implemented in a network apparatus or component, suchas an NE 1000. For instance, the features/methods in the disclosure maybe implemented using hardware, firmware, and/or software installed torun on hardware. The NE 1000 may be any device that transports framesthrough a network, e.g., a switch, router, bridge, server, etc. As shownin FIG. 10, the NE 1000 may comprise a receiver (Rx) 1010 coupled toplurality of ingress ports 1020 for receiving frames from other nodes, alogic unit 1030 coupled to the receiver to determine which nodes to sendthe frames to, and a transmitter (Tx) 1040 coupled to the logic unit1030 and to plurality of egress ports 1050 for transmitting frames tothe other nodes. The logic unit 1030 may comprise one or more multi-coreprocessors and/or memory devices, which may function as data stores. Theingress ports 1020 and/or egress ports 1050 may contain electricaland/or optical transmitting and/or receiving components. NE 1000 may ormay not be a routing component that makes routing decisions.

At least one embodiment is disclosed and variations, combinations,and/or modifications of the embodiment(s) and/or features of theembodiment(s) made by a person having ordinary skill in the art arewithin the scope of the disclosure. Alternative embodiments that resultfrom combining, integrating, and/or omitting features of theembodiment(s) are also within the scope of the disclosure. Wherenumerical ranges or limitations are expressly stated, such expressranges or limitations should be understood to include iterative rangesor limitations of like magnitude falling within the expressly statedranges or limitations (e.g., from about 1 to about 10 includes, 2, 3, 4,etc.; greater than 0.10 includes 0.11, 0.12, 0.13, etc.). For example,whenever a numerical range with a lower limit, R_(l), and an upperlimit, R_(u), is disclosed, any number falling within the range isspecifically disclosed. In particular, the following numbers within therange are specifically disclosed: R=R_(l)+k*(R_(u)−R_(l)), wherein k isa variable ranging from 1 percent to 100 percent with a 1 percentincrement, i.e., k is 1 percent, 2 percent, 3 percent, 4 percent, 7percent, . . . , 70 percent, 71 percent, 72 percent, . . . , 97 percent,96 percent, 97 percent, 98 percent, 99 percent, or 100 percent.Moreover, any numerical range defined by two R numbers as defined in theabove is also specifically disclosed. The use of the term “about”means±10% of the subsequent number, unless otherwise stated. Use of theterm “optionally” with respect to any element of a claim means that theelement is required, or alternatively, the element is not required, bothalternatives being within the scope of the claim. Use of broader termssuch as comprises, includes, and having should be understood to providesupport for narrower terms such as consisting of, consisting essentiallyof, and comprised substantially of. Accordingly, the scope of protectionis not limited by the description set out above but is defined by theclaims that follow, that scope including all equivalents of the subjectmatter of the claims. Each and every claim is incorporated as furtherdisclosure into the specification and the claims are embodiment(s) ofthe present disclosure. The discussion of a reference in the disclosureis not an admission that it is prior art, especially any reference thathas a publication date after the priority date of this application. Thedisclosure of all patents, patent applications, and publications citedin the disclosure are hereby incorporated by reference, to the extentthat they provide exemplary, procedural, or other details supplementaryto the disclosure.

While several embodiments have been provided in the present disclosure,it may be understood that the disclosed systems and methods might beembodied in many other specific forms without departing from the spiritor scope of the present disclosure. The present examples are to beconsidered as illustrative and not restrictive, and the intention is notto be limited to the details given herein. For example, the variouselements or components may be combined or integrated in another systemor certain features may be omitted, or not implemented.

In addition, techniques, systems, and methods described and illustratedin the various embodiments as discrete or separate may be combined orintegrated with other systems, modules, techniques, or methods withoutdeparting from the scope of the present disclosure. Other items shown ordiscussed as coupled or directly coupled or communicating with eachother may be indirectly coupled or communicating through some interface,device, or intermediate component whether electrically, mechanically, orotherwise. Other examples of changes, substitutions, and alterations areascertainable by one skilled in the art and may be made withoutdeparting from the spirit and scope disclosed herein.

What is claimed is:
 1. A user equipment (UE) comprising: a display; an input device configured to receive user input; a visual input configured to capture motion or still photography as visual data; and a processor coupled to the display, the input device, and the visual input, wherein the processor is configured to: receive the visual data from the visual input; overlay a model comprising network data onto the visual data to create a composite image, wherein the network data comprises a position of a network element (NE) and transmission range data associated with the NE, and wherein the model is aligned to the visual data based on user input received from the input device of zooming a view of the model to align to the visual data; transmit the composite image to the display; and display the composite image comprising the position of the NE and the transmission range data associated with the NE.
 2. The UE of claim 1, further comprising a memory device coupled to the processor, wherein the model is received from the memory device prior to overlaying the model onto the visual data.
 3. The UE of claim 1, further comprising a receiver coupled to the processor, wherein the receiver is configured to receive data communications from a server, and wherein the model s received from the server prior to overlaying the model onto the visual data.
 4. The UE of claim 1, wherein the network data is loaded into the model after the model is aligned and prior to overlaying the model onto the visual data.
 5. The UE of claim 4, further comprising a receiver coupled to the processor, wherein the receiver is configured to receive data communications from a server, and wherein the network data is received from the server.
 6. The UE of claim 1, wherein the model comprises a three dimensional (3D) model of a location.
 7. The UE of claim 6, wherein e location is a building.
 8. The UE of claim 1, further comprising position sensors coupled to the processor, wherein the position sensors are configured to indicate UE motion by transmitting motion data to the processor, and wherein the processor is further configured to maintain the model alignment based on the motion data.
 9. The UE of claim 8, wherein the motion data indicates motion of the UE with respect to a horizontal axis, a vertical axis, a lateral axis, or combinations thereof, and wherein the model alignment is maintained by moving the model to correspond with the UE motion.
 10. The UE of claim 9, wherein the motion data comprises measurements, and wherein the congruence of the model and the UE is maintained based on consecutive average measurements.
 11. The UE of claim 9, wherein the model is not visible in a displayed composite image.
 12. A method comprising: importing a model of a location, wherein the location comprises a plurality of physical features, and wherein the model comprises a plurality of features that represent the plurality of physical features of the location; overlaying the model onto a first visual data received from a visual input to create a first composite image and displaying the first composite image to a user; receiving from the user, via an input device, a first user input that aligns a feature of the model with a physical feature of the location in the first visual data by zooming a view of the model to align to the first visual data; loading network data into the model, wherein the network data comprises a position of a network element (NE) and transmission range data associated with the NE; and overlaying the model, as aligned by the user, onto a second visual data received from the visual input to create a second composite image and displaying the second composite image to the user.
 13. The method of claim 12, wherein the model is overlaid onto the first visual data based on a second user input received from the input device.
 14. The method of claim 12, wherein the model comprises position data, and wherein the model is overlaid onto the first visual data based on the position data received from a position sensor.
 15. The method of claim 12, further comprising calibrating to maintain the alignment of the model to the first visual data.
 16. The method of claim 12, wherein the first user input aligns the model feature with the location feature by changing a size or orientation of the model feature to correspond with a size or orientation of the location feature.
 17. The method of claim 12, wherein the model comprises a representation of a geographic area. 